Weronika van Vianen

Weronika van Vianen

Jersey City, New Jersey, United States
812 followers 500+ connections

About

I am a problem-solver who excels and thrives in a challenging and high-pace working…

Activity

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Experience

  • Gecko Robotics, Inc. Graphic

    Gecko Robotics, Inc.

    New York, New York, United States

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    New York, New York, United States

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    New York, New York, United States

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    New York, New York, United States

Education

  • The University of Chicago Booth School of Business Graphic

    The University of Chicago Booth School of Business

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    Activities and Societies: Dean's List each quarter starting with Autumn 2020.

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    2016 class valedictorian
    First undergraduate recipient of the Karl Menger Student Award for Exceptional Scholarship
    Recipient of the College of Science Dean’s Undergraduate Research Stipend
    Full tuition and board merit-based scholarship

Publications

  • Numerical Methods for Estimating Correlation Coe cient of Trivariate Gaussians

    SIAM Undergraduate Research Online (SIURO)

    Given observed data, the fundamental task of statistical inference is to understand the underlying data-generating mechanism. This task usually entails several steps, including determining a good family of probability distributions that could have given rise to the observed data, and identifying the specific distribution from that family that best fits the data. The second step is usually called parameter estimation, where the parameters are what determines the specific distribution. In many…

    Given observed data, the fundamental task of statistical inference is to understand the underlying data-generating mechanism. This task usually entails several steps, including determining a good family of probability distributions that could have given rise to the observed data, and identifying the specific distribution from that family that best fits the data. The second step is usually called parameter estimation, where the parameters are what determines the specific distribution. In many instances, however, estimating parameters of a statistical model poses a significant challenge for statistical inference. Currently, there are many standard optimization methods used for estimating parameters, including numerical approximations such as the Newton-Raphson method. However, they may fail to find a correct set of maximum values of the function and draw incorrect conclusions, since their performance depends on both the geometry of the function and location of the starting point for the approximation. An alternative approach, used in the field of algebraic statistics, involves numerical approximations of the roots of the critical equations by the method of numerical algebraic geometry. This method is used to find all critical points of a function, before choosing the maximum value(s). In this paper, we focus on estimating correlation coe cients for multivariate normal random vectors when the mean is known. The bivariate case was solved in 2000 by Small, Wang and Yang, who emphasize the problem of multiple critical points of the likelihood function. The goal of this paper is to consider the first generalization of their work to the trivariate case, and offer a computational study using both numerical approaches to find the global maximum value of the likelihood function.

    Other authors
    See publication

Projects

  • Optimization of Ebola Treatment Facility Placement in West Africa

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    Over the course of a semester the group developed framework for determining and evaluating results of the SEIR disease model given data with over 10 thousand Ebola infected patients in Liberia. That required a design of an uncertainty quantification model for simulating the most optimal parameters of the SEIR model in the Mathematica programming language. In addition, we applied the CFLP algorithm to find the most optimal locations for the Ebola treatment places in Liberia.

    The project…

    Over the course of a semester the group developed framework for determining and evaluating results of the SEIR disease model given data with over 10 thousand Ebola infected patients in Liberia. That required a design of an uncertainty quantification model for simulating the most optimal parameters of the SEIR model in the Mathematica programming language. In addition, we applied the CFLP algorithm to find the most optimal locations for the Ebola treatment places in Liberia.

    The project resulted with a paper that was presented at PICMath Conference in Washington DC (Summer 2015)

    Other creators
    • Kaelin Cook-Powell
    • Benjamin Grimmer
    • James Panek
    • Nabila Shamshuddin

Honors & Awards

  • Karl Menger Student Award

    Illinois Institute of Technology

    Awarded to one student in the Department of Applied Mathematics for excellence in scholarship.

  • Winner of the Applied Mathematics Poster Competition

    Illinois Institute of Technology

    Poster presentation describing application of my research in "Numerical Methods for Estimating Correlation Coefficient of Trivariate Gaussians" to different scientific fields.

  • College of Science Undergraduate Summer Research Stipends

    Illinois Institue of Technology

    Stipend allowed to conduct 10 weeks during the summer, which resulted in a publication (Numerical Methods for Estimating Correlation Coefficient of Trivariate Gaussians)

Languages

  • English

    Native or bilingual proficiency

  • Polish

    Native or bilingual proficiency

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